PEER-REVIEWED ARTICLE bioresources.com Zhang et al. (2019). “Buckthorn seed extracts,” BioResources 14(1), 2197-2215. 2197 Changes in Components of Aqueous and Non-Aqueous Extracts from Sea Buckthorn Seed Residues through Solid State Fermentation of Monascus purpureus Jia Chan Zhang, a,b Chang Tao Wang, a,b, * Cheng Tao Wang, a,c Shou Xian Wang, d and Bao Guo Sun a,c The feasibility of solid-state fermentation was studied for sea buckthorn seed residues (SBSR). Effects of different fermentation parameters were evaluated regarding the levels of biomass and compounds in aqueous and non-aqueous extracts. In the latent and logarithmic phases of fermentation, the total phenols and flavonoids were increased. The microbes’ decomposition on fibrous matter allowed the active components to be fully extracted. The changes of total sugar levels had a contrary trend with the changes of total phenol and flavonoid contents. The monosaccharide and polypeptide contents decreased dramatically and then kept steady along with the fermentation. Unsuitable environments led to weak growth of the fungi, limited enzyme contents, low enzyme activity, and a poor degradation of the substrates. The active compounds considered in the study were protected, and the contents reached a maximum under conditions that were usually not suitable for the fungal growth. The chemical structure was another important factor influencing the content and stability of the compounds. The content of procyanidins decreased dramatically because of its sensitivity to heat and alkaline environments. Antioxidant abilities of SBSR extracts, both aqueous and non-aqueous, increased after fermentation. These results reflected a possibility to recycle SBSR for further use in the food industry. Keywords: Format; Solid-state fermentation; Sea buckthorn seed residues; Monascus; Fermentative factors; Antioxidant Contact information: a: Beijing Advanced Innovation Center for Food Nutrition and Human Health, Beijing Technology and Business University, Fucheng Road, Beijing 100048, China; b: Beijing Key Lab of Plant Resource Research and Development, Beijing Technology and Business University, Fucheng Road, Beijing 100048, China; c: School of Food and Chemical Engineering of Beijing Technology and Business University, Beijing Higher Institution Engineering Research Center of Food Additives and Ingredients, Fucheng Road, Beijing 100048,China; d: Institute of Plant and Environment Protection, Beijing Academy of Agriculture and Forestry Sciences, Beijing Engineering Research Center for Edible Mushrooms, Shuguang Huayuan Zhonglu, Beijing 100097, China; *Corresponding author: [email protected]INTRODUCTION Sea buckthorn seed residues (SBSR) have been the main by-product of sea buckthorn seed oil processing. These are generally regarded as inexpensive animal feed or organic fertilizers (Arimboor and Arumughan 2012). However, some pharmacological investigations have shown that the extracts of these seed residues still have hypoglycemic, hypotriglyceridemic, and antioxidant properties (Chauhan et al. 2007; Koyama et al. 2009; Zhang et al. 2010a,b), owing to chemically active constituents such as flavonoids, procyanidins, and alkaloids. The SBSR polyphenols extracted with subcritical water show excellent ability to scavenge ABTS (2,2'-azino-bis(3-ethylbenzthiazoline-6-sulphonic
19
Embed
PEER-REVIEWED ARTICLE bioresources · Fermentation, especially solid-state fermentation (SSF), is one of the most rapidly advancing applications to recycle organic wastes (Singhania
This document is posted to help you gain knowledge. Please leave a comment to let me know what you think about it! Share it to your friends and learn new things together.
Changes in Components of Aqueous and Non-Aqueous Extracts from Sea Buckthorn Seed Residues through Solid State Fermentation of Monascus purpureus
Jia Chan Zhang,a,b Chang Tao Wang,a,b,* Cheng Tao Wang,a,c Shou Xian Wang,d and
Bao Guo Sun a,c
The feasibility of solid-state fermentation was studied for sea buckthorn seed residues (SBSR). Effects of different fermentation parameters were evaluated regarding the levels of biomass and compounds in aqueous and non-aqueous extracts. In the latent and logarithmic phases of fermentation, the total phenols and flavonoids were increased. The microbes’ decomposition on fibrous matter allowed the active components to be fully extracted. The changes of total sugar levels had a contrary trend with the changes of total phenol and flavonoid contents. The monosaccharide and polypeptide contents decreased dramatically and then kept steady along with the fermentation. Unsuitable environments led to weak growth of the fungi, limited enzyme contents, low enzyme activity, and a poor degradation of the substrates. The active compounds considered in the study were protected, and the contents reached a maximum under conditions that were usually not suitable for the fungal growth. The chemical structure was another important factor influencing the content and stability of the compounds. The content of procyanidins decreased dramatically because of its sensitivity to heat and alkaline environments. Antioxidant abilities of SBSR extracts, both aqueous and non-aqueous, increased after fermentation. These results reflected a possibility to recycle SBSR for further use in the food industry.
Fig. 1. Effects of fermentation time on biomass (A), non-aqueous bioactive compound content (total phenols, flavonoids, and procyanidins) (B), aqueous monosaccharide and polypeptide content(C) and total sugar (D) content. Each value represents the mean ± SD (n = 3). Values with different superscripts are significantly different (P < 0.05).
Many enzymes secreted by microbes degrade the cell walls of the substrates, which
mobilizes phenols to react with the Folin-Ciocalteu reagent (Wang et al. 2017). The
activities of ligninolytic and cellulosic enzymes were measured, and the results are shown
in Fig. 6. LiP and FPase were the key enzymes catalyzing the oxidative degradation of
lignin and cellulose from SBSR, respectively (Fig. 6A and B). The highest Lip and FPase
activities were obtained on days 9 and 7, respectively. The above results were consistent
with the variation tendency of non-aqueous bioactive compounds (except for procyanidins).
It is known that enzymes have played key roles in breaking the SBSR cell walls, which
leads to the liberation of insoluble-bound phenolics, transforming them into soluble-free
phenolics (Bhanja et al. 2009; Singh et al. 2010). Similar results have been reported (Dey
et al. 2016; Dulf et al. 2016; Huang et al. 2016; Sandhu et al. 2016). A decrease of the total
phenol content was observed after 10 days of fermentation, possibly due to the degradation
of carbon sources (e.g., tannins and phenols) to aliphatic compounds (Saxena et al. 1995;
Bhat et al. 1998). Vattem et al. (2004) pointed out another reason for the decline,
suggesting polymerization of the released phenols by oxidative enzymes, activated as a
response to the stress induced on the fungus due to the nutrient depletion. The total
flavonoid contents increased to the maximum yields of 1.83 ± 0.29 mg RE/g DW after
about 11 days of SSF. Similarly, a substantial increase in the levels of the total flavonoids
activities or the low content of phenol oxidases. Phenol oxidases are distributed widely in
fungi and plants, and they participate in lots of processes such as lignin degradation. The
most prominent phenol oxidases are ligninolytic enzymes, such as laccases (Sinsabaugh
2010). Ligninolytic enzymes not only can liberate insoluble-bound phenolics by breaking
cell walls, they also can catalyze the decomposition of phenol and its derivatives
(Martínková et al. 2016). According to Martínková (2016), tyrosinases are another type of
enzymes playing key roles in degrading phenolics. Results in Fig. 6 (E and F) showed low
activities of ligninolytic and cellulolytic enzymes at 80% water content, which resulted in
weak degradation of phenols. In contrast, the major ligninolytic enzyme in SSF of SBSR
was LiP rather than Lac. This is because that laccase production usually occurs along with
the secondary metabolism of fungi and is influenced by different factors, e.g. substrate
types, culture time, and fungal species (Rivera-Hoyos et al. 2013). It is reported that the
increase in laccase activity occurs together with a codependent increment in fungal growth
(Rivera-Hoyos et al. 2013).
After a period of SSF, the maximum contents of monosaccharides (855.70 ± 31.48
μg GE/g DW) and polypeptide (41.00 ± 2.76 mg/g DW) were all observed at 80% water
content (Fig. 2C). The assumed reason was that the insufficient growth of the fungi led to
less consumption of the nutrients and released a small amount of hydrolases. The total
sugar content got a relatively high level at 60% to 70% water contents (1.63 ± 0.21 mg
GE/g DW to 1.80 ± 0.11 mg GE/g DW), where the fungi M-1 released a large amount of
enzymes to degrade for the growth and reproduction (Fig. 2D). Figures 6E and 6F showed
the enzymes activities at different water contents.
Fig. 2. Effects of water content on biomass (A), non-aqueous bioactive compound content (total phenols, flavonoids, and procyanidins) (B), aqueous monosaccharide and polypeptide content(C) and total sugar (D) content. Each value represents the mean ± SD (n = 3). Values with different superscripts are significantly different (P < 0.05).
Effects of Inoculum Density Many studies have shown the effect of inoculum density on fungal growth or on
product yield in SSF. In this study, the biomass of M-1 was evaluated after a period of
fermentation (Fig. 3A). Inoculating with 1 mL spore suspension ranging from 1.28 × 103
to 3.20 × 104 /mL resulted in insufficient biomass. The results agreed with the theory that
low inoculum density leads to deficient biomass and decreased target product. The
maximum was observed at an inoculum size of 1 mL spore suspension (1.6 × 105 /mL).
There was no significant difference when the inoculum density reached up to 8.00 × 105
spores/mL.
The results of inoculum density on the total phenols, flavonoids, and procyanidins
are shown on Fig. 3B. The maximum contents of total phenols (2.89 ± 0.05 mg GAE/g
DW) and flavonoids (1.87 ± 0.03 mg RE/g DW) were obtained at the inoculum spore
density of 6.4 × 103 /mL, followed by 1.28 × 103 /mL. The amount of procyanidins
decreased with the inoculum density increase. As is well known, high inoculum density is
sufficient for fungi growth and is conducive for the production of enzymes to decompose
carbon sources. Probably, the results were due to the oxidative enzymes (ligninolytic
enzymes, such as LiP) degrading phenols, flavonoids, or procyanidins (Martínková et al.
2016). In the study, the highest activities of ligninolytic and cellulolytic enzymes were both
observed at the inoculum spore density of 8.0 × 105 /mL. However, low activities of LiP
and FPase at low inoculation density were observed (Figs. 6C and D).
Fig. 3. Effects of inoculum size on biomass (A), non-aqueous bioactive compound content (total phenols, flavonoids, and procyanidins) (B), aqueous monosaccharide and polypeptide content(C) and total sugar (D) content. Each value represents the mean ± SD (n = 3). Values with different superscripts are significantly different (P < 0.05).
The contents of the monosaccharides and polypeptides followed a similar tendency.
They all decreased with the increase of inoculum density (Fig. 3C). This was attributed to
the increasing amount of hydrolase (cellulolytic enzymes, such as FPase) released to
degrade these compounds with the increase of the microbes. The total sugars were reduced
at low inoculum density and increased at the density above 3.2 × 104 /mL (Fig. 3D). The
reasons for this phenomenon might be the imbalance between the sugars expended and the
new sugars produced.
Effects of pH Substrate pH is another key parameter to determine microbial growth in SSF. As
for the substrate pH, the Monascus species can grow in a wide range, from 3.0 to 12.0. The
optimal substrate pH varies with the substrate types and fungi species. In this study, the
effects of different substrate pH levels were investigated (Fig. 4A). The optimal pH for
growth was 5.0, with the biomass reaching up to 260.11 ± 11.54 mg glucosamine/g DW.
However, high levels of LiP and FPase activities were observed at pH 7.0 through 9.0 (Figs.
6G and 6H). The results reflected the inconsistency of optimal pH for different purposes.
Babitha et al. (2007) reported that N-acetyl glucosamine concentration was the greatest at
a pH of 5.0 (270 mg/gdfs), when using jack fruit seed as the substrate. These results were
consistent with the present study. At an alkaline pH (9.0 to 12.0), there was a decrease in
the growth profile (Fig. 4A).
Fig. 4. Effects of pH on biomass (A), non-aqueous bioactive compound content (total phenols, flavonoids, and procyanidins) (B), aqueous monosaccharide and polypeptide content(C) and total sugar (D) content. Each value represents the mean ± SD (n = 3). Values with different superscripts are significantly different (P < 0.05).
Figure 4B shows the effects of pH on the total phenols, flavonoids, and
procyanidins in the non-aqueous extracts. The maximum contents were all observed at a
pH of 3.0 (total phenols, flavonoids, and procyanidins were 1.57 ± 0.02 mg GAE/g DW,
1.16 ± 0.03 mg RE/g DW and 2.21 ± 0.07 mg CE/g DW, respectively). Kim et al. (2006)
and Zhao et al. (2017) obtained similar results about the total phenol and flavonoid content.
Each study agreed that lots of combined phenols can be released by hydrolyzing under
acidic conditions. Procyanidins in alkaline conditions showed a dramatic decrease because
of the polyhydroxy structure. It could be easily degraded by oxidative enzymes from
microbes when in a pH range of 5.0 to 7.0.
When discussing the effect of pH, levels of monosaccharides and polypeptides
peaked at both sides and decreased in the middle pH groups (Fig. 4C). The sugar contents
of the substrates peaked at the middle of the pH groups and decreased in acidic conditions
(Fig. 4D). The consistent features were that the declines appeared usually at the point of
the insufficient growth of the fungi. This was assumed to be because a lesser number of
degraded enzymes were generated when there was insufficient growth of microorganisms.
DPPH and ABTS Scavenging Activities Antioxidant activity is strongly connected with the presence of the total phenolics,
flavonoids, anthocyanins, procyanidins, polypeptides, monosaccharides, and other active
compounds (Huang et al. 2013; Chi and Cho 2016; Dulf et al. 2016). Fermentation has a
positive effect on the antioxidant activity of different plant-based matrices, and the degree
of influence depends on the species of the microorganism (Bei et al. 2017; Zhao et al.
2017). In a study by Wang et al. (2017), the DPPH and ABTS* radical-scavenging activity
of fermented guava leaves was dramatically increased because of the increased release of
the total polyphenol components. According to Huang et al. (2013), Monascus purpureus-
fermented residual sorghum showed a remarkable antioxidant activity on mouse embryonic
liver cells.
Fig. 5. DPPH (A) and ABTS* (B) radical scavenging activities of non-aqueous and aqueous extracts at different concentrations. The fermented residues were obtained in the condition as follows: 10 g substrate with 60% water content, adjusted at a pH of 5.0, inoculated 1 mL spore suspension with the density of 3.2 × 104 /mL, and fermented at 28 °C for 15 days. Vc was chosen to be a positive control. Each value represents the mean ± SD (n = 3).
The fermented samples contained plenty of active compounds, as exhibited in Fig.
2 through Fig. 4. It is not a contradiction that there have been no significant correlations
between these active compounds and their antioxidant capacity in previous literature
(Vattem et al. 2004; Kim et al. 2006; Dulf et al. 2016).
Fig. 6. The activities of ligninolytic and cellulosic enzymes in different conditions. The conditions include fermentation time (A, B), inoculum size (C, D), water content (E, F) and pH (G, H). Activities of ligninolytic enzymes (LiP, MnP and Lac) were shown in A, C, E and G. While, activities of cellulosic enzymes (FPase, Avicelase and CMCase) were shown in B, D, F and H. Each value represents the mean ± SD (n = 3).